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Controllability
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== Reachable set == Let T β '''''Π’''''' and x β ''X'' (where X is the set of all possible states and '''''Π’''''' is an interval of time). The reachable set from x in time T is defined as:<ref name=":0" /> <math>R^T{(x)} = \left\{ z \in X : x \overset{T}{\rightarrow} z \right\}</math>, where x{{overset|T|β}}z denotes that there exists a state transition from x to z in time T. For autonomous systems the reachable set is given by : :<math>\mathrm{Im}(R)=\mathrm{Im}(B)+\mathrm{Im}(AB)+....+\mathrm{Im}(A^{n-1}B)</math>, where R is the controllability matrix. In terms of the reachable set, the system is controllable if and only if <math>\mathrm{Im}(R)=\mathbb{R}^n</math>. '''Proof''' We have the following equalities: :<math>R=[B\ AB ....A^{n-1}B]</math> :<math>\mathrm{Im}(R)=\mathrm{Im}([B\ AB ....A^{n-1}B])</math> :<math>\mathrm{dim(Im}(R))=\mathrm{rank}(R)</math> Considering that the system is controllable, the columns of R should be [[linearly independent]]. So: :<math>\mathrm{dim(Im}(R))=n</math> :<math>\mathrm{rank}(R)=n</math> :<math>\mathrm{Im}(R)=\R^{n}\quad \blacksquare</math> A related set to the reachable set is the controllable set, defined by: :<math>C^T{(x)} = \left\{ z \in X : z \overset{T}{\rightarrow} x \right\}</math>. The relation between reachability and controllability is presented by Sontag:<ref name=":0" /> (a) An n-dimensional discrete linear system is controllable if and only if: :: <math>R(0)=R^k{(0)=X}</math> (Where X is the set of all possible values or states of x and k is the time step). (b) A continuous-time linear system is controllable if and only if: :: <math>R(0)=R^e{(0)=X}</math> for all e>0. if and only if <math>C(0)=C^e{(0)=X}</math> for all e>0. '''Example''' Let the system be an n dimensional discrete-time-invariant system from the formula: ::<math>\phi(n,0,0,w)=\sum\limits_{i=1}^n A^{i-1}Bw(n-1)</math> (Where <math>\phi</math>(final time, initial time, state variable, restrictions) is defined as the transition matrix of a state variable x from an initial time 0 to a final time n with some restrictions w). It follows that the future state is in <math>R^k{(0)}</math> if and only if it is in <math>\mathrm{Im}(R)</math>, the image of the linear map <math>R</math>, defined as: ::<math>R(A,B)\triangleq [B\ AB ....A^{n-1}B]</math>, which maps, ::<math>u^{n}\mapsto X</math> When <math>u=K^{m}</math> and <math>X=K^{n}</math> we identify <math>R(A,B)</math> with a <math>n\times nm</math> matrix whose columns are <math>B,\ AB, ....,A^{n-1}B</math> in that order. If the system is controllable the rank of <math>[B\ AB ....A^{n-1}B]</math> is <math>n</math>. If this is true, the image of the linear map <math>R</math> is all of <math>X</math>. Based on that, we have: ::<math>R(0)=R^k{(0)=X}</math> with <math>X\in\R^{n}</math>.
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